blackThe topic of universal portfolio selection is a classical topic in information theory that has been studied for more than three decades, and has been established to have intimate connections to problems like data compression and sequential prediction.
An interested reader is referred to [1]} and the references therein for a detailed treatment of these topics and their interconnections: Chapter 6 explores the horse-race formalism as well as establishes connections between betting on horse races and data compression; Chapters 11 and 13 discuss universal compression and connections to prediction and hypothesis testing; Chapter 14 investigates the closely allied concept of Kolmogorov complexity and the minimum description length (MDL) principle (see also [2]} and [3]} for a detailed treatise on the MDL principle); and Chapter 16 delves into portfolio selection and the UP method. Universal portfolio selection still remains a widely studied topic because a method that simultaneously achieves low regret and low time complexity has been elusive—see [4]}, [5]}, [6]}, [7]} and the references within for recent work in this direction.
